ACREE app adds feature for smarter irrigation decisions
The University of Nebraska-Lincoln and Georgia Institute of Technology have partnered to bring artificial intelligence into farm management through the ACREE app. This latest update introduces a pilot AI feature designed to help producers interpret soil moisture sensor readings more effectively.
The new tool is based on SPADE — Soil moisture Pattern and Anomaly DEtection, which integrates large language models (LLMs) like ChatGPT-4.1. The system can detect irrigation or rainfall events, estimate net water gains in inches, identify anomalies, and create easy-to-read reports for farmers.
Soil moisture sensors often provide multiple data lines at different depths, which can be confusing without calibration. The AI feature simplifies this process by analyzing the past week of readings at 1-foot depth. It identifies missing or extreme values and highlights valid water events, giving farmers a clear picture of what is happening underground.
For instance, SPADE recently detected an irrigation event on August 24 at around 9 a.m. It showed a sharp rise in moisture at the 1-foot depth, from 30.3% to 36.6%. This equaled a moisture gain of about 0.75 inch, with SPADE calculating 0.69 inch. These results provide accurate and timely insight for better irrigation planning.
Developers caution that this is a beta version, and AI tools may make mistakes. Current ACREE users with installed soil moisture sensors can enable the function, while new users should reach out for availability details.
Future releases will include updates powered by ChatGPT-5, offering even more advanced support. By combining sensor data with AI technology, this innovation gives farmers new confidence in managing irrigation and improving crop efficiency.
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